Colour schemes in data visualisation: Bias and Precision
The technique of mapping continuous values to a sequence of colours, is often used to visualise quantitative data. The ability of different colour schemes to facilitate data interpretation has not been thoroughly tested. Using a survey framework built with Shiny and loggr, we compared six commonly used colour schemes in two experiments: a measure of perceptually linearity and a map reading task for: (1) bias and precision in data interpretation, (2) response time and (3) colour preferences. The single-hue schemes were unbiased — perceived values did not consistently deviate from the true value, but very imprecise — large data variance between the perceived values. Schemes with hue transitions improved precision, however they were highly biased when not close to perceptually linearity (especially for the multi-hue 'rainbow' schemes). Response time was shorter for the single-hue schemes and longer for more complex colour schemes. There was no aesthetic preference for any of the colourful schemes. These results show that in choosing a colour scheme to communicate quantitative information, there are two potential pitfalls: bias and precision. Every use of colour to represent data should be aware of the bias--precision trade-off and select the scheme that balances these two potential communication errors.